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NVIDIA NeMo Speech Developer Docs
=================================
`NVIDIA NeMo Speech <https://github.com/NVIDIA/NeMo>`_ is an open-source toolkit for speech, audio, and multimodal language model research, with a clear path from experimentation to production deployment.
.. raw:: html
<style>
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.task-card { border: 1px solid #e0e0e0; border-radius: 8px; padding: 20px; text-decoration: none !important; color: inherit !important; transition: box-shadow 0.2s; }
.task-card:hover { box-shadow: 0 4px 12px rgba(0,0,0,0.1); }
.task-card h3 { margin-top: 0; }
.task-card p { color: #555; font-size: 0.95em; }
</style>
<div class="task-card-grid">
<a class="task-card" href="asr/intro.html">
<h3>🎙️ Transcribe Speech (ASR)</h3>
<p>Convert audio to text with state-of-the-art accuracy. Supports 14+ languages, streaming, and timestamps.</p>
<strong>Quick Start →</strong>
</a>
<a class="task-card" href="tts/intro.html">
<h3>🔊 Synthesize Speech (TTS)</h3>
<p>Generate natural human speech from text. Multi-language, multi-speaker, with controllable prosody.</p>
<strong>Quick Start →</strong>
</a>
<a class="task-card" href="asr/speaker_diarization/intro.html">
<h3>👥 Identify Speakers</h3>
<p>Determine "who spoke when" in multi-speaker audio. Speaker diarization, recognition, and verification.</p>
<strong>Quick Start →</strong>
</a>
<a class="task-card" href="speechlm2/intro.html">
<h3>🧠 Speech Language Models</h3>
<p>Audio-aware LLMs that understand and generate speech. Use HuggingFace Transformers, or NeMo Automodel for efficient MoE and model parallelism. Speech-to-text, speech-to-speech, and more.</p>
<strong>Quick Start →</strong>
</a>
<a class="task-card" href="audio/intro.html">
<h3>🎧 Process Audio</h3>
<p>Enhance, restore, and separate audio signals. Improve audio quality for downstream tasks.</p>
<strong>Quick Start →</strong>
</a>
<a class="task-card" href="tools/intro.html">
<h3>🛠️ Speech AI Tools</h3>
<p>Forced alignment, data exploration, CTC segmentation, and evaluation utilities for speech workflows.</p>
<strong>Explore Tools →</strong>
</a>
</div>
What is NeMo?
--------------
`NVIDIA NeMo <https://github.com/NVIDIA/NeMo>`_ is an open-source toolkit for building, customizing, and deploying speech, audio, and multimodal language models. It provides:
- **Pretrained models** — production-ready checkpoints on `NGC <https://catalog.ngc.nvidia.com/models?query=nemo&orderBy=weightPopularDESC>`__ and `HuggingFace Hub <https://huggingface.co/nvidia>`__
- **Modular architecture** — neural modules you can mix, match, and extend
- **Scalable training** — multi-GPU/multi-node via PyTorch Lightning with mixed-precision support
- **Simple configuration** — YAML-based experiment configs with `Hydra <https://hydra.cc/>`__
Get started (install the PyTorch build for your platform first):
.. code-block:: bash
uv pip install 'nemo-toolkit[asr,tts]'
.. code-block:: python
import nemo.collections.asr as nemo_asr
model = nemo_asr.models.ASRModel.from_pretrained("nvidia/parakeet-tdt-0.6b-v2")
print(model.transcribe(["audio.wav"])[0].text)
Trying to finetune a model?
---------------------------
Check out our latest ``/nemo-speech-finetune-asr`` `agent skill <https://github.com/NVIDIA-NeMo/NeMo/tree/main/.claude/skills/nemo-speech-asr-finetune>`_.
.. toctree::
:maxdepth: 1
:caption: Getting Started
:name: starthere
starthere/install
starthere/ten_minutes
starthere/key_concepts
starthere/choosing_a_model
starthere/tutorials
.. toctree::
:maxdepth: 1
:caption: Training
:name: Training
features/parallelisms
features/mixed_precision
checkpoints/intro
dataloaders
.. toctree::
:maxdepth: 1
:caption: Collections
:name: Collections
:titlesonly:
asr/intro
tts/intro
speechlm2/intro
asr/speaker_diarization/intro
asr/speaker_recognition/intro
audio/intro
asr/ssl/intro
asr/speech_classification/intro
.. toctree::
:maxdepth: 1
:caption: Speech AI Tools
:name: Speech AI Tools
:titlesonly:
tools/nemo_forced_aligner
tools/ctc_segmentation
tools/speech_data_explorer
tools/comparison_tool
tools/asr_evaluator
tools/speech_data_processor
.. toctree::
:maxdepth: 1
:caption: APIs
:name: APIs
:titlesonly:
core/core
core/neural_modules
core/exp_manager
core/neural_types
core/adapters/intro
core/api
common/intro
asr/api
tts/api
audio/api